Causality and causal inference in epidemiology: the need for a pluralistic approach.
about
Treating the host response to emerging virus diseases: lessons learned from sepsis, pneumonia, influenza and Ebola.From paediatrics to geriatrics: a life course perspective on the MRC National Survey of Health and DevelopmentOn wagging tales about causal inferenceQuestioning the application of risk of bias tools in appraising evidence from natural experimental studies: critical reflections on Benton et al., IJBNPA 2016Commentary: The formal approach to quantitative causal inference in epidemiology: misguided or misrepresented?The Consistency Assumption for Causal Inference in Social Epidemiology: When a Rose is Not a Rose.Clinical epidemiology: A daydream?Health Claims and Methodological Controversy in Nutrition Science.Response: Formalism or pluralism? A reply to commentaries on 'Causality and causal inference in epidemiology'.Post-traumatic stress disorder and cardiometabolic disease: improving causal inference to inform practice.Causal inference-so much more than statistics.Causation, mediation and explanation.What is in a name? Does cancer subtyping help or hinder in epidemiology research?Trade-offs of Personal Versus More Proxy Exposure Measures in Environmental Epidemiology.Triangulation in aetiological epidemiology.Race, obesity, and birth outcomes: Unraveling a complex association to improve maternal-child health.Does water kill? A call for less casual causal inferences.Causality and causal inference in epidemiology: we need also to address causes of effects.Counterfactual and interventionist approach to cure risk factor epidemiology.Caution: work in progress : While the methodological "revolution" deserves in-depth study, clinical researchers and senior epidemiologists should not be disenfranchised.Cohort Profile: The Heinz C. Prechter Longitudinal Study of Bipolar Disorder.Do pregnancy characteristics contribute to rising childhood cancer incidence rates in the United States?Rating the quality of a body of evidence on the effectiveness of health and social interventions: a systematic review and mapping of evidence domains.Hill's Heuristics and Explanatory Coherentism in Epidemiology.Best Practices for Gauging Evidence of Causality in Air Pollution Epidemiology.A concern over terminology in vaccine effectiveness studies.Commentary: Counterfactual causation and streetlamps: what is to be done?Author's reply: The role of potential outcomes thinking in assessing mediation and interaction.Commentary: On Causes, Causal Inference, and Potential Outcomes.Evaluating the potential role of pleiotropy in Mendelian randomization studiesPersonalization of medicine requires better observational evidence
P2860
Q28076034-842D3683-B3F0-4C88-9453-83C4ED1A2C7FQ28584508-38B814DC-440C-4758-8F4A-BB9E58396EDAQ30224334-9145A773-D004-4957-AE57-CFD78FE8DC40Q33582506-6616F047-AE07-4DFE-BCC2-4F30DADF695BQ36263026-1A2098F8-05DF-4F87-8383-18E7660983D2Q37016178-9FA7372B-2F89-42EF-9E93-2DE6C85F6914Q37730977-FEF6B131-447D-4CC8-8387-B6F300817EA2Q38768153-C1B22003-3548-4E4E-9577-DB1AB8F877DDQ38921770-8F27CC8A-13E0-46A0-8D72-FE9F738E05D7Q38970920-EBFD18A4-AF9F-40C2-8C69-64F607B6589EQ39345142-CEED2E52-D796-43A9-AD80-97FCF2E99853Q39345149-862D96E7-EEFF-4019-B058-6FB374E9D3C1Q40141643-549D4C96-E8D8-4EF7-99CC-C5B7CD5C4F1DQ40196887-FC4CA65A-9182-4664-B7DF-C423928B7626Q40370721-02756F80-C917-4BEE-B89D-A9CBC5FFDD32Q40454737-ABB8F4BD-A978-4038-B5E4-F70E49BA95BEQ40509610-9DEF4869-B5E3-4AF3-8504-414E7C63835FQ40622149-6F8E2749-9F78-4B8A-BD1E-59D4FAAC4125Q40622159-F2D95904-F70E-4334-9A9E-FF7C3AAD0AF5Q40650606-80F1DB2C-9D6D-49D0-ACC5-58F75C937173Q47276941-BCEAD96E-9B38-4A5C-9D39-29CC79929659Q47436213-180F9BE9-596C-4E23-8045-D457E97F4F14Q47557608-B8D6B241-4FE2-4CF5-90A5-34CCD611DB50Q47625304-4C3AADCC-CA45-4F75-9D75-AC85D0F8E11FQ50094001-474C9AF8-5CA2-47AE-8F2D-4C3215222DE2Q54256218-E1905364-1F52-4DA2-A3B5-12A3A955F456Q54289711-57530A5A-2AE6-4A9B-8914-403DAB6DADC9Q54943427-892C99C8-7E25-4A2A-937A-E6413FC4819FQ55304448-13116772-9C16-49EE-914B-E8DFC1BFD0BAQ57101556-248C9EE5-2C48-48D4-B3EC-B6CFACEDEDD0Q57484442-C5D7194F-8D84-4565-9891-A3B6BB2575FC
P2860
Causality and causal inference in epidemiology: the need for a pluralistic approach.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
Causality and causal inference in epidemiology: the need for a pluralistic approach.
@en
Causality and causal inference in epidemiology: the need for a pluralistic approach.
@nl
type
label
Causality and causal inference in epidemiology: the need for a pluralistic approach.
@en
Causality and causal inference in epidemiology: the need for a pluralistic approach.
@nl
prefLabel
Causality and causal inference in epidemiology: the need for a pluralistic approach.
@en
Causality and causal inference in epidemiology: the need for a pluralistic approach.
@nl
P2860
P356
P1476
Causality and causal inference in epidemiology: the need for a pluralistic approach
@en
P2093
Jan P Vandenbroucke
P2860
P304
P356
10.1093/IJE/DYV341
P577
2016-12-01T00:00:00Z